• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.652-653
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• 2011

수요반응(DR : Demand Response)은 스마트 그리드(Smart Grid)를 구성하는 핵심 요소 중 하나이다. 본 논문에서는 스마트 그리드 환경 하에서 ISO(Independent System Operator)의 수요자원시장에 참여함과 동시에 말단 수용가들을 대상으로 다수의 DR 프로그램을 운영하는 LA(Load Aggregator)사업자의 DR자원 운영 시스템에 대한 전반적인 개념 및 흐름에 대하여 기술하였다. 또한, 스마트 그리드 하에서 LA사업자의 DR자원 운영 시스템 설계 중 LA사업자의 DR자원 최적배분 전략에 대한 개념 및 예시를 제시하였다.

• Journal of Satellite, Information and Communications
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• v.7 no.2
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• pp.1-7
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• 2012

In recent years, importance of environmental protection and energy resources has increased. Therefore, eco - friendly consumption patterns is rapidly increased. Accordingly, efficient energy consumption technology is noted in a variety of industries. Smart grid technology can improve energy efficiency by using IT technology. Among them, the demand response is an critical factor in the smart grid. In this paper, we present basic concept of smart grid and demand response. In addition, we present demand response technology and its application examples.

• Journal of the Korean Data and Information Science Society
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• v.20 no.2
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• pp.283-292
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• 2009

Recently the stable electric power supply is threaten by the rapid development of all the industries consuming a lot of electric power, thus KEPCO is trying to establish the countermeasures to cope with this circumstance of uprising power consumption by running the efficient and flexible 12-month s price policy for the base price and raisin the electric power price remarkably in peak power consumption period to suppress the maximal power demand of consumers. To resolve these problems, this study propose the method calculating hourly CBL based on the hourly amount at non-event using the pattern of the amount of power consumption and propose the operation method of DR Program.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.365-371
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• 2021

In this study, The Virtual Power Plant (VPP) solution platform considered in this study minimizes the cost and investment risk associated with the construction of power generation and transmission facilities. In addition, it includes a Demand Response (DR) program operation function to meet consumers' electricity demand. With the introduction of VPP, it is possible to provide more eco-friendly and efficient power by responding to changes in consumer load in real time through existing generators and DR programs without large-scale facility investment in power generation and transmission/distribution sectors. In order to link the communication device to the solar power and ESS linkage device, it is necessary to transmit data in the control/state between the device device and the edge system and develop an IoT device and interworking platform (OneM2M).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.117-124
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• 2017

A Smart Grid is a system that can efficiently use energy by exchanging real-time information in both directions between a consumer and a power supplier using ICT technology on an existing power network. DR(Demand response) is an arrangement in which electricity users can sell the electricity they save to the electricity market when the price of electricity is high or the power system is crisis. In this study, we developed a power meter data transmission device and power IT system that measure the demand information in real-time using a smart meter and transmit it to a cloud server. The power meter data transmission device developed in this study uses alight sensor connected to a Raspberry Pi 3 to measure the number of blinking lamps on the KEPCO meter per unit of power, in order to provide reliable data without any measurement errors with respect to the KEPCO power data. The power measurement data transmission device uses the standard communication protocol, OpenADR 2.0b. The measured data is transmitted to the power IT system, which consists of the VEN, VTN, and calculation program, via the LTE WiFi communication network and stored in its MySQL DB. The developed power measurement data transmission device issues a power supply instruction and performs a peak reduction DR when a power system crisis occurs. The developed power meter data transmission device has the advantage of allowing the user to adjust it every 1 minute, where as the existing smart metering time is fixed at once every 15 minutes.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.2
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• pp.329-333
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• 2021

V2G (Vehicle to Grid) technology for an EV (Electric Vehicle) has been assumed as so promising in a near future for its useful energy resource concept but still yet to be developed around the world for specific service purposes through various R&BD projects. Basically, V2G returns power stored in vehicle at a cheaper or unused time to the grid at more expensive or highly peaked time, and is accordingly supposed to provide such roles like peak shaving or load levelling according to customer load curve, frequency regulation or ancillary reserves, and balancing power fluctuation to grid from the weather-sensitive renewable sources like wind or solar generations. However, it has recently been debated over its prominent usage as diffusing EVs and the required charging/discharging infrastructure, partially for its addition of EV ownership costs with more frequent charging/discharging events and user inconvenience with a relative long-time participation in the previously engaged V2G program. This study suggests that a Korean DR (Demand Response) service integrated V2G system especially based upon a dynamic charge/pause/discharge scheme newly proposed to ISO/IEC 15118 rev. 2 can deal with these concerns with more profitable business model, while fully making up for the additional component (ex. battery) and service costs. It also indicates that the optimum economic, environmental, and grid impacts can be simulated for this V2G-DR service particularly designed for EV aggregators (V2G service providers) by proposing a specific V2G engagement program for the mediated DR service providers and the distributed EV owners.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.68-77
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• 2018

Regarding demand response (DR) by residential users (R-users), the users try to reduce electricity costs by adjusting their power consumption in response to the time-varying price. However, their power consumption may be affected not only by the price, but also by user convenience for using appliances. This paper proposes a methodology for appliance scheduling (AS) that considers the user convenience based on historical data. The usage pattern for appliances is first modeled applying the copula function or clustering method to evaluate user convenience. As the modeling results, the comfort distribution or representative scenarios are obtained, and then used to formulate a discomfort index (DI) to assess the degree of the user convenience. An AS optimization problem is formulated in terms of cost and DI. In the case study, various AS tasks are performed depending on the weights for cost and DI. The results show that user convenience has significant impacts on AS. The proposed methodology can contribute to induce more DR participation from R-users by reflecting properly user convenience to AS problem.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.1
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• pp.28-34
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• 2009

In this study firstly we survey the calculation method and the characteristics of the way of estimating CBL(Customer BaseLine Load) that is important calculation tool for DRP internationally. Also we analyze the power consumption pattern using the 15 minutes load profiles of about 120,000 customers in domestic. Based on this pattern, we provide the CBL calculation method that can be utilized in DRP to save the cost, and analyze the accuracy of the CBL calculation proposed in this paper through the simulation.

• Journal of Information Technology Services
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• v.21 no.6
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• pp.117-125
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• 2022

In respond to climate change caused by global environmental problems, countries around the world are actively promoting the advancement of new electricity industries. The new energy business is being applied to energy storage systems (ESS), electric vehicle charging business, and power demand response using cutting edge technologies. In 2022, the Korean government is also establishing a policy stance to foster new energy industries and making efforts to improve its responsiveness to power demand response with the innovative technologies. In Korea, attempts to commercialize energy power are also being made in the private and public sectors to control energy power in houses, buildings, and industries. For example, private companies, local governments, and central government are making all-out efforts to develop new energy industry models through joint investment. There are forms such as establishing energy-independent facilities by region, establishing an electric vehicle charging system, controlling urban lighting systems with Information technologies, and managing demand between power suppliers and power consumers. This study examined the business model applied with energy storage system, electric vehicle charging business, smart lighting, and power demand response based on information communication technology to examine the site where smart energy system was introduced. According to this study, company missions and government tasks are suggested to apply new energy business technologies as economical energy solutions that meet the purpose of use by region, industry, and company.

• Journal of the HCI Society of Korea
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• v.12 no.4
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• pp.65-73
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• 2017

While electricity demand is generally increasing, stably controlling supply is becoming a serious challenge because renewable energies are becoming popular and often their productions are dependent on the weather. The 'demand response' programs can be used to complement the problems of renewable energies, and therefore their role is becoming increasingly important. This study provides an analysis of a demand response pilot that was conducted in Korea. The study first focused on questionnaire surveys and in-depth interviews, and the data was used to perform a Technology Acceptance Model (TAM) analysis. The goal of the pilot was to have the residential users reduce their power consumptions when an energy reduction mission is issued during peak load hours. The experimental subjects consisted of two groups with different characteristics. Subjects in group A obtained smart meters as an optional function of IoT platform service provided by a mobile service company, and received a charge deduction as their compensation. Subjects in group B either voluntarily purchased smart meters as individuals or received them by participating in an energy self-sufficient village program that was run by a local government, and were entitled to a donation as their compensation. With the analysis, group A was found to fit the extended technology acceptance model that includes perceived playfulness in addition to perceived ease of use and perceived usefulness. On the contrary, group B failed to fit the model well, but perceived usefulness was found to be relatively more important compared to group A. The results indicate that the residential energy groups' behavior changes are dependent on each group's characteristics, and group-specific DR design should be considered to improve the effectiveness of DR.